Investigating the Topology Dependence of Quark and Gluon Jets

Abstract

As most target final states for searches and measurements at the Large Hadron Collider have a particular quark/gluon composition, tools for distinguishing quark- from gluon-initiated jets can be very powerful. In addition to the difficulty of the classification task, quark-versus-gluon jet tagging is challenging to calibrate. The difficulty arises from the topology dependence of quark-versus-gluon jet tagging: since quarks and gluons have net quantum chromodynamic color charge while only colorless hadrons are measured, the radiation pattern inside a jet of a particular type depends on the rest of its environment. Given a definition of a quark or gluon jet, this paper studies the topology dependence of such jets in simulation. A set of phase space regions and jet substructure observables are identified for further comparative studies between generators and eventually in data.

arXiv comment24 pages, 10 figures

References in corpus (27)

• The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
• The anti-k_t jet clustering algorithm
• A Brief Introduction to PYTHIA 8.1
• FastJet user manual
• Herwig 7.0 / Herwig++ 3.0 Release Note
• Jet substructure as a new Higgs search channel at the LHC
• Soft Drop
• Jet Trimming
• Towards an understanding of jet substructure
• Classification without labels: Learning from mixed samples in high energy physics
• Deep learning in color: towards automated quark/gluon jet discrimination
• Gaining (Mutual) Information about Quark/Gluon Discrimination
• Quark and Gluon Tagging at the LHC
• Non-perturbative QCD effects in jets at hadron colliders
• Seeing in Color: Jet Superstructure
• Systematics of quark/gluon tagging
• Small-radius jets to all orders in QCD
• Quark and Gluon Jet Substructure
• Factorization for groomed jet substructure beyond the next-to-leading logarithm
• On the Topic of Jets: Disentangling Quarks and Gluons at Colliders
• Casimir Meets Poisson: Improved Quark/Gluon Discrimination with Counting Observables
• Weakly Supervised Classification in High Energy Physics
• Recursive Neural Networks in Quark/Gluon Tagging
• An operational definition of quark and gluon jets
• Dissecting Soft Radiation with Factorization
• Improving the Simulation of Quark and Gluon Jets with Herwig 7
• QCD-aware partonic jet clustering for truth-jet flavour labelling

Cited by in corpus (21)

• Jet Substructure at the Large Hadron Collider: Experimental Review
• OmniFold: A Method to Simultaneously Unfold All Observables
• A measurement of soft-drop jet observables in $pp$ collisions with the ATLAS detector at $\sqrt{s}=13$ TeV
• Quark-Gluon Tagging: Machine Learning vs Detector
• Deep-Learning Jets with Uncertainties and More
• Supervised Jet Clustering with Graph Neural Networks for Lorentz Boosted Bosons
• Per-Object Systematics using Deep-Learned Calibration
• Quarks and gluons in the Lund plane
• Properties of jet fragmentation using charged particles measured with the ATLAS detector in $pp$ collisions at $\sqrt{s}=13$ TeV
• Disentangling Quarks and Gluons with CMS Open Data
• Improving Generative Model-based Unfolding with Schrödinger Bridges
• Combine and Conquer: Event Reconstruction with Bayesian Ensemble Neural Networks
• CapsNets Continuing the Convolutional Quest
• A Method to Simultaneously Facilitate All Jet Physics Tasks
• Solving Key Challenges in Collider Physics with Foundation Models
• Lund multiplicity in QCD jets
• Dynamic Radius Jet Clustering Algorithm
• Going off topics to demix quark and gluon jets in ${\alpha }_S$ extractions
• TopicFlow: Disentangling quark and gluon jets with normalizing flows
• Improving Heavy Dijet Resonance Searches Using Jet Substructure at the LHC
• Quark-versus-gluon tagging in CMS Open Data with CWoLa and TopicFlow